code: def test_fabric_run_executor_mps_forced_cpu(
      accelerator_given, accelerator_expected
  ):
      warning_str = r"Forcing `accelerator=cpu` as MPS does not support distributed training."
      if accelerator_expected != accelerator_given:
          warning_context = pytest.warns(UserWarning, match=warning_str)
      else:
          warning_context = no_warning_call(match=warning_str + "*")
  
      with warning_context:
          ret_val, _ = _get_args_after_tracer_injection(
              accelerator=accelerator_given
          )
      assert ret_val["accelerator"] == accelerator_expected
  
file_path: pytorch-lightning/tests/tests_app/components/multi_node/test_fabric.py
imports: import os
  from copy import deepcopy
  from functools import partial
  from unittest import mock
  import lightning.fabric
  import pytest
  from lightning.app.components.multi_node.fabric import _FabricRunExecutor
  from lightning_utilities.core.imports import module_available
  from lightning_utilities.test.warning import no_warning_call
label_desc: Use image node_id 5 for calling a global function with example usage: test_fabric_run_executor_mps_forced_cpu(accelerator_given, accelerator_expected) without return types